Machine Learning Engineer

Raven Development; Comisión de Fomento de Perú; Hybrid; ARS 139,364,000 - 201,304,000; Full time

Job summary

Ravn is hiring an ML Engineer to own how machine learning models move from experiment to production. You will design pipelines, infrastructure, and practices to deploy and monitor ML models in the cloud, including GenAI workloads, with cost-efficient strategies.

Responsibilities include building CI/CD for ML, implementing MLOps, managing environments, and collaborating with data scientists and engineers to integrate models into production APIs. Remote Latin America option available.

Qualifications

• Bachelor’s degree in computer science, mathematics, computational linguistics, or a similar field (or equivalent practical experience).
• 5+ years of experience in ML engineering, MLOps, or a closely related role.
• Demonstrated experience deploying and operating ML systems at scale.
• Strong Python skills, and solid experience with SQL and NoSQL databases.
• Strong backend engineering background in at least one modern language or framework (Python, Node.js, Go, .NET, Java, or similar).
• Hands‑on experience with CI/CD tooling (e.g., GitHub Actions, GitLab CI, Jenkins) and containerization (Docker, Kubernetes).
• Experience working in a microservices or distributed‑systems environment.
• Strong written and verbal communication skills in English.
• Ability to adapt to changing business and project priorities.

Responsibilities

• Design, build, and maintain automated pipelines to deploy, monitor, and iterate on ML models in the cloud, including classical ML and LLM/GenAI workloads.
• Build and own CI/CD for ML (training, testing, validation, release, rollback) using modern tooling.
• Implement MLOps best practices: experiment tracking, model versioning and registries, reproducibility, and observability (drift, performance, data quality).
• Manage dependency and environment standards (Python packaging, containers) across ML projects.
• Provision and manage cloud infrastructure for training and inference workloads, using infrastructure-as-code.
• Develop and apply strategies to optimize cloud and compute costs (right-sizing, autoscaling, spot/serverless, GPU utilization).
• Partner with data scientists, backend engineers, and product teams to integrate models into production services and APIs.

Skills

Python

SQL

NoSQL

Microservices

English communication

Education

Bachelor’s degree in CS/Math/Computational Linguistics or related

Tools

Docker

Kubernetes

GitHub Actions

Jenkins

Terraform

Job description

Ravn is a digital product development agency that partners with companies to build exceptional software. We specialize in building and designing world-class mobile and web applications and seek exceptional engineers to join our company.

At Ravn, we do quality work at lightning speed. The only way to consistently meet requirements with confidence is to hire people who share a passion for technology and are focused on building software the right way. We deliver digital solutions - done right, on time, every time.

We’re looking for an ML Engineer to own how machine learning models get from experiment to production. You’ll build the pipelines, infrastructure, and practices that let our teams ship and operate models, including LLM-based and GenAI features, reliably, quickly, and cost-effectively in the cloud.

Responsibilities

Design, build, and maintain automated pipelines to deploy, monitor, and iterate on ML models in the cloud, including classical ML and LLM/GenAI workloads

Build and own CI/CD for ML (training, testing, validation, release, rollback) using modern tooling

Implement MLOps best practices: experiment tracking, model versioning and registries, reproducibility, and observability (drift, performance, data quality)

Manage dependency and environment standards (Python packaging, containers) across ML projects

Provision and manage cloud infrastructure for training and inference workloads, using infrastructure-as-code

Develop and apply strategies to optimize cloud and compute costs (right-sizing, autoscaling, spot/serverless, GPU utilization)

Partner with data scientists, backend engineers, and product teams to integrate models into production services and APIs

Qualifications

Bachelor’s degree in computer science, mathematics, computational linguistics, or a similar field (or equivalent practical experience)

5+ years of experience in ML engineering, MLOps, or a closely related role

Demonstrated experience deploying and operating ML systems at scale

Strong Python skills, and solid experience with SQL and NoSQL databases

Strong backend engineering background in at least one modern language or framework (Python, Node.js, Go, .NET, Java, or similar). We care more about engineering fundamentals than a specific stack

Hands‑on experience with CI/CD tooling (e.g., GitHub Actions, GitLab CI, Jenkins) and containerization (Docker, Kubernetes)

Experience working in a microservices or distributed‑systems environment

Strong written and verbal communication skills in English

Ability to adapt to changing business and project priorities

Nice to Have

Experience with LLM/GenAI systems (RAG, vector databases, prompt/eval pipelines, model serving)

Experience with ML platforms and tooling (e.g., MLflow, SageMaker, Vertex AI, Kubeflow, Airflow)

Experience with serverless technologies

Infrastructure‑as‑code experience (Terraform, CloudFormation, or similar)

Cloud certification (e.g., AWS Solutions Architect or equivalent)

Location:

This position is open to candidates based anywhere in Latin America and is fully remote. Candidates located near our offices in Arequipa, Peru or San Salvador, El Salvador have the option to work in a hybrid in‑office/remote arrangement. While office attendance is not mandatory, regular or occasional visits to the office are valued.